The state of health (SOH) estimation of lithiumion batteries at a low sampling frequency has great significance in engineering applications. The concepts of regional voltage (ΔV) and regional sampling points (RSP) are introduced, and an evaluation method of lithium-ion battery SOH under the framework of probability density function (PDF) is proposed. A battery SOH evaluation model based on RSP was established based on the laboratory cycle ageing data of lithium-iron phosphate (LFP) batteries. The RSP method and the traditional PDF method were compared, and the effects of the RSP-SOH models under different sampling frequencies and regional voltages were investigated. The results show that the RSP-SOH model has a linear positive correlation with SOH, and the effect of RSP-SOH model is better than that of the traditional PDF method under both charging and discharging conditions. The evaluation effect of the RSP-SOH model can be improved by increasing the region voltage appropriately when the sampling frequency is low. The battery RSP-SOH model is robust to the sampling frequency under the charging condition, and the R2 of the model is greater than 0.98 under the low sampling frequency of one sampling point every five minutes. On this basis, the SOH of 220 LFP batteries in an energy storage power station is relatively evaluated by using the regional sampling point method. When nine batteries with smaller RSP are replaced, the power handling capacity of the energy storage station will increase by 20.9%.